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DTSTART:19700308T020000
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DTSTAMP:20260417T190156Z
LOCATION:East Building\, Room 11
DTSTART;TZID=America/Los_Angeles:20250811T104500
DTEND;TZID=America/Los_Angeles:20250811T171500
UID:siggraph_SIGGRAPH 2025_sess277_twork_105@linklings.com
SUMMARY:Generalizing Natural Behavior: Retargeting Human or Animal Motion 
 to Robotic Forms
DESCRIPTION:Farbod Farshidian, Jean Pierre Sleiman, Yunbo Zhang, and Jessi
 ca Hodgins (Robotics and AI Institute); Moritz Bächer (Disney Research); Y
 uting Ye (Reality Labs Research, Meta); Naureen Mahmood (Meshcapade GmbH);
  Xue Bin Peng (Simon Fraser University); and Michiel Van de Panne (Univers
 ity of British Columbia)\n\nLegged robots, particularly humanoids, represe
 nt an emerging technology whose widespread acceptance depends on their abi
 lity to perform meaningful tasks at the human cadence in the real world. W
 hile human motion data can drive progress in this field, it is often spars
 e and lacks action labels, limiting the effectiveness of supervised learni
 ng. Recent advancements in imitation learning, reinforcement learning, and
  robotic hardware improvements have led to better generalization of natura
 l behaviors in robots. This workshop will bring together leaders in human/
 animal simulation, control, animation, and robotics to discuss the state-o
 f-the-art techniques for natural motion generation of physics-based charac
 ters and robots.\n\nInterest Area: Research & Education\n\nRecording: Not 
 Livestreamed, Not Recorded\n\nKeyword: Animation, Physical AI, Robotics\n\
 nRegistration Category: Full Conference, Experience\n\n
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